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# CosineAnnealingParamScheduler¶

class mmengine.optim.CosineAnnealingParamScheduler(optimizer, param_name, T_max=None, eta_min=None, begin=0, end=1000000000, last_step=- 1, by_epoch=True, verbose=False, eta_min_ratio=None)[源代码]

Set the parameter value of each parameter group using a cosine annealing schedule, where $$\eta_{max}$$ is set to the initial value and $$T_{cur}$$ is the number of epochs since the last restart in SGDR:

\begin{split}\begin{aligned} \eta_t & = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + \cos\left(\frac{T_{cur}}{T_{max}}\pi\right)\right), & T_{cur} \neq (2k+1)T_{max}; \\ \eta_{t+1} & = \eta_{t} + \frac{1}{2}(\eta_{max} - \eta_{min}) \left(1 - \cos\left(\frac{1}{T_{max}}\pi\right)\right), & T_{cur} = (2k+1)T_{max}. \end{aligned}\end{split}

Notice that because the schedule is defined recursively, the parameter value can be simultaneously modified outside this scheduler by other operators. If the parameter value is set solely by this scheduler, the parameter value at each step becomes:

$\eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + \cos\left(\frac{T_{cur}}{T_{max}}\pi\right)\right)$

It has been proposed in SGDR: Stochastic Gradient Descent with Warm Restarts. Note that this only implements the cosine annealing part of SGDR, and not the restarts.

• optimizer (Optimizer or BaseOptimWrapper) – optimizer or Wrapped optimizer.

• param_name (str) – Name of the parameter to be adjusted, such as lr, momentum.

• T_max (int, optional) – Maximum number of iterations. If not specified, use end - begin. Defaults to None.

• eta_min (float, optional) – Minimum parameter value. Defaults to None.

• begin (int) – Step at which to start updating the parameters. Defaults to 0.

• end (int) – Step at which to stop updating the parameters. Defaults to INF.

• last_step (int) – The index of last step. Used for resume without state dict. Defaults to -1.

• by_epoch (bool) – Whether the scheduled parameters are updated by epochs. Defaults to True.

• verbose (bool) – Whether to print the value for each update. Defaults to False.

• eta_min_ratio (float, optional) – The ratio of the minimum parameter value to the base parameter value. Either eta_min or eta_min_ratio should be specified. Defaults to None. New in version 0.3.2.

classmethod build_iter_from_epoch(*args, T_max=None, begin=0, end=1000000000, by_epoch=True, epoch_length=None, **kwargs)[源代码]

Build an iter-based instance of this scheduler from an epoch-based config.

© Copyright 2022, mmengine contributors. Revision 0549e1ce.

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